Effect of Precipitator and Desulphurization Devices on the Removal of Mercury with Different Speciation in Coal-fired Flue Gas
Bibliographic record
Abstract
Ontario-Hydro method was employed to determine the concentration and speciation of mercury in the flue-gas emitted from a coal-fired boiler equipped with electrostatic precipitator(ESP) and wet flue gas desulphurization(WFGD).The mass balance of mercury was calculated.The results indicate that HgP could be removed efficiently by ESP.The removal efficiencies of Hg2+、Hg0 and total mercury by WFGD were 81.3%、53.8% and 62.1%,respectively.Mercury mainly emits as Hg0 with a percentage of more than 80% of total mercury.The total mercury balance was 91.17% between the coal and its combustion products.It was verified that the flue-gas cleaning devices of coal-fired power plant had significant impacts on mercury emission characteristics,which could be helpful to develop the integrated technology for precipitator,desulphurization and mercury removal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".